Development and Implementation of Some Controllers for Performance Enhancement and Effective Utilization of Induction Motor Drive

The technological development in the field of power electronics and DSP technology is rapidly changing the aspect of drive technology. Implementations of advanced control strategies like field oriented control, linearization control, etc. to AC drives with variable voltage, and variable frequency source is possible because of the advent of high modulating frequency PWM inverters. The modeling complexity in the drive system and the subsequent requirement for modern control algorithms are being easily taken care by high computational power, low-cost DSP controllers. The present work is directed to study, design, development, and implementation of various controllers and their comparative evaluations to identify the proper controller for high-performance induction motor (IM) drives. The dynamic modeling for decoupling control of IM is developed by making the flux and torque decoupled. The simulation is carried out in the stationary reference frame with linearized control based on state-space linearization technique. Further, comprehensive and systematic design procedures are derived to tune the PI controllers for both electrical and mechanical subsystems. However, the PI-controller performance is not satisfactory under various disturbances and system uncertainties. Also, precise mathematical model, gain values, and continuous tuning are required for the controller design to obtain high performance. Thus, to overcome these drawbacks, an adapted control strategy based on Adaptive Neuro-Fuzzy Inference System (ANFIS) based controller is developed and implemented in real-time to validate different control strategies. The superiority of the proposed controller is analyzed and is contrasted with the conventional PI controller-based linearized IM drive. The simplified neuro-fuzzy control (NFC) integrates the concept of fuzzy logic and neural network structure like conventional NFC, but it has the advantages of simplicity and improved computational efficiency over conventional NFC as the single input introduced here is an error instead of two inputs error and change in error as in conventional NFC. This structure makes the proposed NFC robust and simple as compared to conventional NFC and thus, can be easily applied to real-time industrial applications. The proposed system incorporated with different control methods is also validated with extensive experimental results using DSP2812. The effectiveness of the proposed method using feedback linearization of IM drive is investigated in simulation as well as in experiment with different working modes. It is evident from the comparative results that the system performance is not deteriorated using proposed simplified NFC as compared to the conventional NFC, rather it shows superior performance over PI-controller-based drive. A hybrid fuel cell (FC) supply system to deliver the power demanded by the feedback linearization (FBL) based IM drive is designed and implemented. The modified simple hybrid neuro-fuzzy sliding-mode control (NFSMC) incorporated with the intuitive FBL substantially reduces torque chattering and improves speed response, giving optimal drive performance under system uncertainties and disturbances. This novel technique also has the benefit of reduced computational burden over conventional NFSMC and thus, suitable for real-time industrial applications. The parameters of the modified NFC is tuned by an adaptive mechanism based on sliding-mode control (SMC). A FC stack with a dc/dc boost converter is considered here as a separate external source during interruption of main supply for maintaining the supply to the motor drive control through the inverter, thereby reducing the burden and average rating of the inverter. A rechargeable battery used as an energy storage supplements the FC during different operating conditions of the drive system. The effectiveness of the proposed method using FC-based linearized IM drive is investigated in simulation, and the efficacy of the proposed controller is validated in real-time. It is evident from the results that the system provides optimal dynamic performance in terms of ripples, overshoot, and settling time responses and is robust in terms of parameters variation and external load

Graph Signal Processing: Overview, Challenges and Applications

Research in Graph Signal Processing (GSP) aims to develop tools for processing data defined on irregular graph domains. In this paper we first provide an overview of core ideas in GSP and their connection to conventional digital signal processing. We then summarize recent developments in developing basic GSP tools, including methods for sampling, filtering or graph learning. Next, we review progress in several application areas using GSP, including processing and analysis of sensor network data, biological data, and applications to image processing and machine learning. We finish by providing a brief historical perspective to highlight how concepts recently developed in GSP build on top of prior research in other areas.Comment: To appear, Proceedings of the IEE

A 2x2 bit multiplier using hybrid 13t full adder with vedic mathematics method

Various arithmetic circuits such as multipliers require full adder (FA) as the main block for the circuit to operate. Speed and energy consumption become very vital in design consideration for a low power adder. In this paper, a 2x2 bit Vedic multiplier using hybrid full adder (HFA) with 13 transistors (13T) had been designed successfully. The design was simulated using Synopsys Custom Tools in General Purpose Design Kit (GPDK) 90 nm CMOS technology process. In this design, four AND gates and two hybrid FA (HFAs) are cascaded together and each HFA is constructed from three modules. The cascaded module is arranged in the Vedic mathematics algorithm. This algorithm satisfied the requirement of a fast multiplication operation because of the vertical and crosswise architecture from the Urdhva Triyakbyam Sutra which reduced the number of partial products compared to the conventional multiplication algorithm. With the combination of hybrid full adder and Vedic mathematics, a new combination of multiplier method with low power and low delay is produced. Performance parameters such as power consumption and delay were compared to some of the existing designs. With a 1V voltage supply, the average power consumption of the proposed multiplier was found to be 22.96 µW and a delay of 161 ps

A fast and retargetable framework for logic-IP-internal electromigration assessment comprehending advanced waveform effects

A new methodology for system-on-chip-level logic-IP-internal electromigration verification is presented in this paper, which significantly improves accuracy by comprehending the impact of the parasitic RC loading and voltage-dependent pin capacitance in the library model. It additionally provides an on-the-fly retargeting capability for reliability constraints by allowing arbitrary specifications of lifetimes, temperatures, voltages, and failure rates, as well as interoperability of the IPs across foundries. The characterization part of the methodology is expedited through the intelligent IP-response modeling. The ultimate benefit of the proposed approach is demonstrated on a 28-nm design by providing an on-the-fly specification of retargeted reliability constraints. The results show a high correlation with SPICE and were obtained with an order of magnitude reduction in the verification runtime.Peer ReviewedPostprint (author's final draft

Power conversion for a modular lightweight direct-drive wind turbine generator

A power conversion system for a modular lightweight direct-drive wind turbine generator has been proposed, based on a modular cascaded multilevel voltage-source inverter. Each module of the inverter is connected to two generator coils, which eliminates the problem of DC-link voltage balancing found in multilevel inverters with a large number of levels.The slotless design of the generator, and modular inverter, means that a high output voltage can be achieved from the inverter, while using standard components in the modules. Analysis of the high voltage issues shows that isolating the modules to a high voltage is easily possible, but insulating the generator coils could result in a signicant increase in the airgap size, reducing the generator effciency. A boost rectier input to the modules was calculated to have the highest electrical effciency of all the rectier systems tested, as well as the highest annual power extraction, while having a competitive cost. A rectier control system, based on estimating the generator EMF from the coil current and drawing a sinusoidal current in phase with the EMF, was developed. The control system can mitigate the problem of airgap eccentricity, likely to be present in a lightweight generator. A laboratory test rig was developed, based on two 2.5kW generators, with 12 coils each. A single phase of the inverter, with 12 power modules, was implemented, with each module featuring it's own microcontroller. The system is able to produce a good quality AC voltage waveform, and is able to tolerate the fault of a single module during operation. A decentralised inverter control system was developed, based on all modules estimating the grid voltage position and synchronising their estimates. Distributed output current limiting was also implemented, and the system is capable of riding through grid faults

Signal processing for molecular and cellular biological physics:an emerging field

Recent advances in our ability to watch the molecular and cellular processes of life in action-such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer-raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied

Control of switched reluctance machines

This thesis is concerned with the control of switched reluctance machines for both motoring and generating applications. There are different control objectives in each case. For motoring operation, there are two possible control objectives. If the SRM is being employed in a servo-type application, the desire is for a constant output torque. However, for low performance applications where some amount of torque ripple is acceptable, the aim is to achieve efficient and accurate speed regulation. When the SRM is employed for generating purposes, the goal is to maintain the dc bus voltage at the required value while achieving maximum efficiency. Preliminary investigative work on switched reluctance machine control in both motoring and generating modes is performed. This includes the implementation and testing through simulation of two control strategies described in the literature. In addition, an experimental system is built for the development and testing of new control strategies. The inherent nonlinearity of the switched reluctance machine results in ripple in the torque profile. This adversely affects motoring performance for servo-type applications. Hence, three neuro-fuzzy control strategies for torque ripple minimisation in switched reluctance motors are developed. For all three control strategies, the training of a neurofuzzy compensator and the incorporation of the trained compensator into the overall switched reluctance drive are described. The performance of the control strategies in reducing the torque ripple is examined with simulations and through experimental testing. While the torque ripple is troublesome for servo-type applications, there are some applications where a certain amount of torque ripple is acceptable. Therefore, four simple motor control strategies for torque ripple-tolerant applications are described and tested experimentally. Three of the control strategies are for low speed motoring operation while the fourth is aimed at high speed motoring operation. Finally, three closed-loop generator control strategies aimed at high speed operation in single pulse mode are developed. The three control strategies are examined by testing on the experimental system. A comparison of the performance of the control strategies in terms of efficiency and peak current produced by each is presented